A01=Dolores DeGroff
A01=P. S. Neelakanta
AA Unit
advanced neural network theory
Author_Dolores DeGroff
Author_P. S. Neelakanta
Boltzmann Machine
brain dynamics
Category=GPFC
Category=UYQN
Cellular Automata
cognitive systems
complex
computational neuroscience
Dolores F. De Groff
Entropy Space
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Hopfield's Model
Hopfield’s Model
Interspike Interval
Interspike Interval Distribution
Ising Spin
Ising Spin Model
Ising Spin System
Logical Neuron
Long Range Order
Low Pass Action
mathematical biology
McCulloch Pitts Neuron
Nematic Phase
Neural Assembly
Neural Complex
Neuronal Assembly
Neuronal Transmission
Perambur S. Neelakanta
Real Neurons
Self-organizing Architecture
Single Spin Flips
Spin System
State Transition Process
statistical modeling
stochastic processes
Stochastical Perspectives
Product details
- ISBN 9780849324888
- Weight: 630g
- Dimensions: 156 x 234mm
- Publication Date: 12 Jul 1994
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.
Neelakanta, P. S.; DeGroff, Dolores
